1. Field of the Invention
The present invention relates to a neurofilter, which is a non-linear filter implemented as a neural network, and to a method of training a neurofilter to produce an output signal which discriminates between text and picture regions of an image expressed by image data which are supplied to the neurofilter.
The invention further relates to a filter apparatus in which a neurofilter is utilized to compensate for errors in the output signal from a conventional filter.
2. Prior Art
In the prior art, it has been necessary for designers of filters, for such applications as serial signal processing or image data processing, to have extensive experience in that field of work. This is due to the fact that considerable experience is necessary, to enable the designer to set the filter parameters to optimum values. Setting of the filter parameters is difficult, due to the fact that in general the transfer function of a filter is non-linear. Hence, it is necessary to use linear approximation functions to establish a preliminary design of a filter, and for the designer to then try to optimize the design by modifying the values of the filter parameters, on the basis of his experience.
Hence, in the prior art, the degree to which the performance of a filter approached optiumum has been dependent upon the experience of the filter designer, i.e. in general it has not been possible for other individuals to design a filter.
Furthermore even in the case of an experienced filter designer, due to the various forms of non-linearity of operation of an actual filter, it has been impossible to actually achieve optimum results.